OBJECTIVETo investigate the co-culture of keratinocytes with Malassezia isolates which cause the pityriasis versicolor with different color and to analyze the changes of cytokines associated with melanogenesis.

METHODSThe effects of Malassezia species with different proportions on the growth rate of keratinocytes was assessed with 5 g/L methyl thiazolyl tetrazolium (MTT). Co-culture of keratinocytes and Malassezia species were performed with isolates from hyer- and hypo-pigmentation areas of pityriasis versicolor. The supernatants were collected at different time points, and the changes of basic fibroblast growth factor (b-FGF), endothelin-1 (ET-1), nerve growth factor-beta (NGF-beta), interleukin-1alpha (IL-1alpha), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-alpha), stem cell factor (SCF) were recorded. Three control groups were established accordingly.

RESULTSWhen the ratio between keratinocytes and Malassezia species was lower than 1: 10, the growth rate of keratinocytes was not affected by Malassezia (P > 0.05). When the ratio was increased above 1:20, the growth rate of keratinocytes was significantly inhibited by Malassezia (P < 0.01). The secretions of IL-1alpha, IL-6, TNF-alpha, and ET-1 was significantly increased after the co-culture of keratinocytes and Malassezia (P < 0.01), while those of b-FGF, NGF-beta, and SCF had no significant changes (P > 0.05). Compared with the isolates from the hypo-pigmentation area, ET-1 induced by isolate from hyperpigmentation area significantly increased (P < 0.01).

CONCLUSIONWhen Malassezia isolates are co-cultured with keratinocytes, the secretions of cytokines associated with melanogenesis may differ from each other. ET-1 may play certain role in the hyper-pigmentation of pityriasis versicolor.

Cell Proliferation ; Cells, Cultured ; Cytokines ; biosynthesis ; Humans ; Keratinocytes ; cytology ; metabolism ; microbiology ; Malassezia ; isolation & purification ; physiology ; Melanins ; biosynthesis ; Tinea Versicolor ; microbiology

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI).
Algorithms ; Cell Line ; Chondrocytes/cytology/metabolism/microbiology ; Databases, Genetic ; Gene Expression Profiling ; Host-Pathogen Interactions ; Humans ; Keratinocytes/cytology/metabolism/microbiology ; *Models, Genetic ; Mycoplasma/genetics/metabolism ; Oligonucleotide Array Sequence Analysis